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DBMS > Databricks vs. EsgynDB vs. Heroic vs. SWC-DB

System Properties Comparison Databricks vs. EsgynDB vs. Heroic vs. SWC-DB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonHeroic  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websitewww.databricks.comwww.esgyn.cngithub.com/­spotify/­heroicgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.databricks.comspotify.github.io/­heroic
DeveloperDatabricksEsgynSpotifyAlex Kashirin
Initial release2013201520142020
Current release0.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaC++
Server operating systemshostedLinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesnonono
Secondary indexesyesyesyes infovia Elasticsearch
SQL infoSupport of SQLwith Databricks SQLyesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Proprietary protocol
Thrift
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC++
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored Proceduresnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEsgynDBHeroicSWC-DB infoSuper Wide Column Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEsgynDBHeroicSWC-DB infoSuper Wide Column Database
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